Project/Area Number |
20240016
|
Research Category |
Grant-in-Aid for Scientific Research (A)
|
Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Intelligent informatics
|
Research Institution | National Institute of Informatics |
Principal Investigator |
INOUE Katsumi 国立情報学研究所, 情報学プリンシプル研究系, 教授 (10252321)
|
Co-Investigator(Kenkyū-buntansha) |
SATO Taisuke 東京工業大学, 大学院・情報理工学研究科, 教授 (90272690)
KAMEYA Yoshitaka 東京工業大学, 大学院・情報理工学研究科, 助教 (60361789)
IWANUMA Koji 山梨大学, 大学院・医学工学総合研究部, 教授 (30176557)
NABESHIMA Hidetomo 山梨大学, 大学院・医学工学総合研究部, 准教授 (10334848)
YAMAMOTO Yoshitaka 山梨大学, 大学院・医学工学総合研究部, 助教 (30550793)
SAKAMA Chiaki 和歌山大学, システム工学部, 教授 (20273873)
|
Co-Investigator(Renkei-kenkyūsha) |
FUJIYAMA Asao 国立情報学研究所, 情報学プリンシプル研究系, 教授 (60142311)
|
Project Period (FY) |
2008 – 2011
|
Project Status |
Completed (Fiscal Year 2011)
|
Budget Amount *help |
¥34,060,000 (Direct Cost: ¥26,200,000、Indirect Cost: ¥7,860,000)
Fiscal Year 2011: ¥8,710,000 (Direct Cost: ¥6,700,000、Indirect Cost: ¥2,010,000)
Fiscal Year 2010: ¥8,190,000 (Direct Cost: ¥6,300,000、Indirect Cost: ¥1,890,000)
Fiscal Year 2009: ¥8,060,000 (Direct Cost: ¥6,200,000、Indirect Cost: ¥1,860,000)
Fiscal Year 2008: ¥9,100,000 (Direct Cost: ¥7,000,000、Indirect Cost: ¥2,100,000)
|
Keywords | 人工知能 / 推論 / システム生物学 / 仮説発見 / 結論発見 / 確率推論 / 帰納論理プログラミング / アブダクション |
Research Abstract |
Systems biology is an emergent field that aims to understand living organisms as biological systems. To find useful information from biological data, we focus on inference methods, induction and abduction, based on logic-based Artificial Intelligence. Both abduction and induction are used to infer hypotheses in inductive logic programming(ILP), and can be implemented using the consequence finding procedure SOLAR. However, in the current inference methods, efficiency of inference needs to be improved, and mechanisms for hypotheses selection are necessarily developed. Hence, the following three subtasks are set in this project: (1) Improving hypothesis finding methods based on SOLAR and related techniques; (2) Developing effective hypothesis selection methods based on both statistical and non-statistical approaches; (3) Applying those methods to problems in systems biology.
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